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Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057924/ https://www.ncbi.nlm.nih.gov/pubmed/33898733 http://dx.doi.org/10.1016/j.imu.2021.100578 |
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author | Khan, Md. Tahsin Islam, Md. Jahirul Parihar, Arpana Islam, Rahatul Jerin, Tarhima Jahan Dhote, Rupali Ali, Md. Ackas Laura, Fariha Khan Halim, Mohammad A. |
author_facet | Khan, Md. Tahsin Islam, Md. Jahirul Parihar, Arpana Islam, Rahatul Jerin, Tarhima Jahan Dhote, Rupali Ali, Md. Ackas Laura, Fariha Khan Halim, Mohammad A. |
author_sort | Khan, Md. Tahsin |
collection | PubMed |
description | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status. |
format | Online Article Text |
id | pubmed-8057924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80579242021-04-21 Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 Khan, Md. Tahsin Islam, Md. Jahirul Parihar, Arpana Islam, Rahatul Jerin, Tarhima Jahan Dhote, Rupali Ali, Md. Ackas Laura, Fariha Khan Halim, Mohammad A. Inform Med Unlocked Article Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmittable and pathogenic human coronavirus that caused a pandemic situation of acute respiratory syndrome, called COVID-19, which has posed a significant threat to global health security. The aim of the present study is to computationally design an effective peptide-based multi-epitope vaccine (MEV) against SARS-CoV-2. The overall model quality of the vaccine candidate, immunogenicity, allergenicity, and physiochemical analysis have been conducted and validated. Molecular dynamics studies confirmed the stability of the candidate vaccine. The docked complexes during the simulation revealed a strong and stable binding interactions of MEV with human and mice toll-like receptors (TLR), TLR3 and TLR4. Finally, candidate vaccine codons have been optimized for their in silico cloning in E. coli expression system, to confirm increased expression. The proposed MEV can be a potential candidate against SARS-CoV-2, but experimental validation is needed to ensure its safety and immunogenicity status. The Authors. Published by Elsevier Ltd. 2021 2021-04-21 /pmc/articles/PMC8057924/ /pubmed/33898733 http://dx.doi.org/10.1016/j.imu.2021.100578 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Khan, Md. Tahsin Islam, Md. Jahirul Parihar, Arpana Islam, Rahatul Jerin, Tarhima Jahan Dhote, Rupali Ali, Md. Ackas Laura, Fariha Khan Halim, Mohammad A. Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title | Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title_full | Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title_fullStr | Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title_full_unstemmed | Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title_short | Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2 |
title_sort | immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for sars-cov-2 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057924/ https://www.ncbi.nlm.nih.gov/pubmed/33898733 http://dx.doi.org/10.1016/j.imu.2021.100578 |
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